The main hypothesis of this work is that the time of delay in reaction to an unexpected event can be predicted on the basis of the brain activity recorded prior to that event. Such mental activity can be represented by electroencephalographic data. To test this hypothesis, we conducted a novel experiment involving 19 participants that took part in a 2-h long session of simulated aircraft flights. An EEG signal processing pipeline is proposed that consists of signal preprocessing, extracting bandpass features, and using regression to predict the reaction times. The prediction algorithms that are used in this study are the Least Absolute Shrinkage Operator and its Least Angle Regression modification, as well as Kernel Ridge and Radial Basis Support Vector Machine regression. The average Mean Absolute Error obtained across the 19 subjects was 114 ms. The present study demonstrates, for the first time, that it is possible to predict reaction times on the basis of EEG data. The presented solution can serve as a foundation for a system that can, in the future, increase the safety of air traffic.

中文翻译：

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基于脑电信号的飞行员反应时间预测

这项工作的主要假设是，可以根据事件发生之前记录的大脑活动来预测对意外事件的反应延迟时间。这种心理活动可以用脑电图数据表示。为了验证这一假设，我们进行了一项新颖的实验，涉及 19 名参与者，这些参与者参加了 2 小时的模拟飞机飞行。提出了一种 EEG 信号处理流程，包括信号预处理、提取带通特征和使用回归预测反应时间。本研究中使用的预测算法是最小绝对收缩算子及其最小角度回归修正，以及核脊和径向基支持向量机回归。在 19 名受试者中获得的平均平均绝对误差为 114 毫秒。本研究首次表明，可以根据 EEG 数据预测反应时间。所提出的解决方案可以作为系统的基础，在未来可以提高空中交通的安全性。